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Atlas was developed by Netflix to manage dimensional time series data for near real-time operational insight. Atlas features in-memory data storage, allowing it to gather and report very large numbers of metrics, very quickly. 

Atlas captures operational intelligence. Whereas business intelligence is data gathered for the purpose of analyzing trends over time, operational intelligence provides a picture of what is currently happening within a system.

Atlas was built because the existing systems Netflix was using for operational intelligence were not able to cope with the increase in metrics we were seeing as we expanded our operations in the cloud. In 2011, we were monitoring 2 million metrics related to our streaming systems. By 2014, we were at 1.2 billion metrics and the numbers continue to rise. Atlas is designed to handle this large quantity of data and can scale with the hardware we use to analyze and store it. 

For details and background on the project please read through the [[Overview]] page. 

Check out the [[Getting Started]] page for an introduction to using Atlas in the cloud environment. Once you've explored the example, check out the stack language references to see the various types of information you can access.